A number of researchers have developed learning systems that can be
viewed as considering evidence from neighboring regions of the instance
space in order to derive classifications within regions of the
instance space that are not occupied by examples from the training
set.
Ting [1994] does this explicitly, by examining the
training set to directly explore the neighborhood of the object to be
classified. This system uses instance based
learning for classification within nodes of a decision tree with
low empirical support (small disjuncts).

A number of other systems can also be viewed as considering evidence
from neighboring regions for classification. These systems learn
and then apply multiple classifiers
[Ali, Brunk, and Pazzani, 1994,
Nock and Gascuel, 1995,
Oliver and Hand, 1995]. In such a
context, any point within a region of the instance space that is
occupied by no training objects is likely to be covered by multiple
leaves or rules. Of these, the leaf or rule with the greatest
empirical support will be used for classification.

C4.5X uses two distinct criteria for evaluating potential splits.
The standard C4.5 stage of tree induction employs an information
measure to select splits. The post-processor uses a Laplace accuracy
estimate. Similar uses of dual criteria have been investigated elsewhere.
Quinlan [1991] employs a Laplace accuracy estimate considering
neighboring regions of the instance space to estimate the accuracy of
small disjuncts. Lubinsky [1995] and
Brodley [1995] employ
resubstitution accuracy to select splits near the leaves during
induction of decision trees.

By adding a split to a leaf, C4.5X is specializing with respect to the
class at that leaf (and generalizing with respect to the class of the
new leaf).
Holte [1993] explored a number of techniques for
specializing small disjuncts. C4.5X differs in that all leaves are
candidates for specialization, not just those with low empirical
support. It further differs in the manner in which it selects the
specialization to perform by considering the evidence in support of
alternative splits rather than just the strength of the evidence in
support of individual potential conditions for the current disjunct.